Research Paper Volume 12, Issue 6 pp 5259—5279
Whole-transcriptome analysis reveals a potential hsa_circ_0001955/hsa_circ_0000977-mediated miRNA-mRNA regulatory sub-network in colorectal cancer
- 1 Department of Breast Surgery, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, Zhejiang Province, China
- 2 Program of Innovative Cancer Therapeutics, Division of Hepatobiliary and Pancreatic Surgery, Department of Surgery, First Affiliated Hospital, College of Medicine, Zhejiang University, Key Laboratory of Organ Transplantation, Hangzhou, Zhejiang Province, China
- 3 Key Laboratory of Organ Transplantation, Hangzhou, Zhejiang Province, China
- 4 Key Laboratory of Combined Multi-organ Transplantation, Ministry of Public Health, Hangzhou, Zhejiang Province, China
Received: December 24, 2019 Accepted: March 9, 2020 Published: March 28, 2020https://doi.org/10.18632/aging.102945
How to Cite
Copyright © 2020 Ding et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Background: Circular RNAs (circRNAs), a novel class of non-coding RNAs, have been found to act as microRNA (miRNA) sponges and thus play key roles in biological processes and pathogenesis. However, studies regarding circRNAs in colorectal cancer (CRC) remain inadequate.
Results: By differential expression analysis, 10 candidate circRNAs (6 upregulated and 4 downregulated circRNAs) were chosen. 9 of 10 circRNAs were available on CSCD and their structure showed the binding potential of miRNA. Intersection analysis revealed that miR-145-5p, miR-3127-5p, miR-761, miR-4766-3p, miR-135a-5p, miR-135b-5p, miR-374a-3p and miR-330-3p were 8 miRNAs with the most potential in binding circRNAs. Further expression validation and correlation analysis demonstrated hsa_circ_0001955/miR-145-5p and hsa_circ_0000977/miR-135b-5p axes as key pathways in CRC. Subsequently, target gene prediction, differential expression analysis, intersection analysis and correlation analysis showed that CDK6, MMP12 and RAB3IP were the three potential downstream targets of hsa_circ_0001955/miR-145-5p axis and FOXO1, MBNL1, MEF2C, RECK, PPM1E, TTLL7 and PCP4L1 were the seven potential downstream targets of hsa_circ_0000977/miR-135b-5p axis in CRC. Finally, we also confirmed that expression of hsa_circ_0001955 or hsa_circ_0000977 was significantly positively correlated with their individual targets in CRC.
Conclusions: In the present work, we constructed a potential hsa_circ_0001955/hsa_circ_0000977-mediated circRNA-miRNA-mRNA regulatory network in CRC by a series of in silico analysis and experimental validation.
Methods: Whole-transcriptome microarrays from CRC and matched normal samples were obtained from GEO. The structure of circRNA was identified by CSCD. starBase and miRNet were successively used to predict miRNA of circRNA and target gene of miRNA. Expression correlation between RNA-RNA interactions was assessed using GEO and TCGA data. Finally, a potential circRNA-miRNA-mRNA network was established based on competing endogenous RNA (ceRNA) hypothesis.